Application of Adaptive Particle Swarm Optimization to Bi - level Job - Shop Scheduling Problem

Chompoonoot Kasemset 대한산업공학회 2014 Industrial Engineeering & Management Systems Vol.13 No.1

This study presents an application of adaptive particle swarm optimization (APSO) to solving the bi-level job-shop scheduling problem (JSP). The test problem presented here is 10×10 JSP (ten jobs and ten machines) with tribottleneck machines formulated as a bi-level formulation. APSO is used to solve the test problem and the result is compared with the result solved by basic PSO. The results of the test problem show that the results from APSO are significantly different when compared with the result from basic PSO in terms of the upper level objective value and the iteration number in which the best solution is first identified, but there is no significant difference in the lower objective value. These results confirmed that the quality of solutions from APSO is better than the basic PSO. Moreover, APSO can be used directly on a new problem instance without the exercise to select parameters.

Traffic Information Sign Location Problem: Optimization and Simulation

Chompoonoot Kasemset,Chawis Boonmee,Masahiro Arakawa 대한산업공학회 2020 Industrial Engineeering & Management Systems Vol.19 No.1

Traffic congestion is a critical problem in many big cities when expansion of traffic systems is implemented to catch up with the increasing demand for road transportation. The policy to shift routes to avoid traffic congestion is one policy that can be supported by traffic information systems. A traffic information sign is one of the solutions that provide traffic information to drivers (users) for selecting routes. Infrastructure for physical signs needs investment, so the optimal number and location of signs should be appropriate for maximizing the effectiveness in reducing traffic congestion. Firstly, a mathematical model for the location of traffic signs was proposed in this study. Then optimal solutions were evaluated using simulation tests. Application of the proposed method is presented for solving the case study of Chiang Mai University’s traffic network. The optimal solutions were to assign two signs on roads with high departure flows and high possibility to change directions. The simulation results present ranges of the probability for changing directions that can reduce the departure flows at the bottleneck gate. When the flows at the bottleneck gate were reduced, the traffic in this area was shown to be less congested. Moreover, utilizations of gates were more balanced.

A Risk Management Framework for New Product Development: A Case Study

Chompoonoot Kasemset,Jaruwan Wannagoat,Wassanai Wattanutchariya,Korrakot Y. Tippayawong 대한산업공학회 2014 Industrial Engineeering & Management Systems Vol.13 No.2

This research designed and implemented a supply chain risk management platform and applied it to a case study of reduced-fat Lanna pork sausage as a new product development project. The proposed framework has three stages: risk identification, risk assessment, and risk mitigation. Seventeen risk agents with 17 risk events were identified based on SWOT analysis and the Porter Five Forces concept through the process of planning, sourcing, making and delivering, partially captured from the supply chain operations reference model in the first stage. In the second stage, an house of risk (HOR) framework was applied to present the impacts of each risk agent. In the third stage, eight risk agents with high impact were selected to design 21 preventive actions. Finally, three preventive actions with the highest effectiveness to difficulty ratio scores-‘sales evaluation of familiar products’, ‘increasing distribution channels and promotions to improve sales’, and ‘work flow improvement for work safety’-were then recommended for this new product development.

Application of Adaptive Particle Swarm Optimization to Bi-level Job-Shop Scheduling Problem

Kasemset, Chompoonoot Korean Institute of Industrial Engineers 2014 Industrial Engineeering & Management Systems Vol.13 No.1

This study presents an application of adaptive particle swarm optimization (APSO) to solving the bi-level job-shop scheduling problem (JSP). The test problem presented here is $10{\times}10$ JSP (ten jobs and ten machines) with tribottleneck machines formulated as a bi-level formulation. APSO is used to solve the test problem and the result is compared with the result solved by basic PSO. The results of the test problem show that the results from APSO are significantly different when compared with the result from basic PSO in terms of the upper level objective value and the iteration number in which the best solution is first identified, but there is no significant difference in the lower objective value. These results confirmed that the quality of solutions from APSO is better than the basic PSO. Moreover, APSO can be used directly on a new problem instance without the exercise to select parameters.

A Risk Management Framework for New Product Development: A Case Study

Kasemset, Chompoonoot,Wannagoat, Jaruwan,Wattanutchariya, Wassanai,Tippayawong, Korrakot Y. Korean Institute of Industrial Engineers 2014 Industrial Engineeering & Management Systems Vol.13 No.2

This research designed and implemented a supply chain risk management platform and applied it to a case study of reduced-fat Lanna pork sausage as a new product development project. The proposed framework has three stages: risk identification, risk assessment, and risk mitigation. Seventeen risk agents with 17 risk events were identified based on SWOT analysis and the Porter Five Forces concept through the process of planning, sourcing, making and delivering, partially captured from the supply chain operations reference model in the first stage. In the second stage, an house of risk (HOR) framework was applied to present the impacts of each risk agent. In the third stage, eight risk agents with high impact were selected to design 21 preventive actions. Finally, three preventive actions with the highest effectiveness to difficulty ratio scores-'sales evaluation of familiar products', 'increasing distribution channels and promotions to improve sales', and 'work flow improvement for work safety'-were then recommended for this new product development.

The Multi-Objective Fuzzy Mathematical Programming Model for Humanitarian Relief Logistics

Chawis Boonmee,Chompoonoot Kasemset 대한산업공학회 2020 Industrial Engineeering & Management Systems Vol.19 No.1

The concern about humanitarian relief logistics has spurred an interest in disaster management. The use of warehouses for storing relief items is one of the most important parts that can help the victims immediately during a disaster occurrence. Effective warehouse location selection is quite difficult since there are several criteria such as budget, response time, and uncertainty of data. Thus, this study aims to propose a multi-objective fuzzy mathematical programming model for humanitarian relief logistics. This study presents an integrated facility location problem, inventory problem and distribution problem in humanitarian relief logistics under consideration of the inherent uncertainty of input parameters. The proposed model focuses on minimization of the response time and the planning budget that determines the location of warehouses, total inventory to be stored in each warehouse, distributed management of the warehouses, and the holding utilization of the warehouses. To solve the proposed multi-objective optimization model with fuzzy parameters, an equivalent auxiliary crisp model and an epsilon constraint approach are adopted in this study. A real case study in Pichit province, Thailand, is employed to validate the proposed model. Finally, the results are proposed and discussed that represent several alternatives to decision makers.

Radiotherapy Service Improvement: Simulation Study

Chawis Boonmee,Auttharat Kosayanon,Imjai Chitapanarux,Chompoonoot Kasemset 대한산업공학회 2020 Industrial Engineeering & Management Systems Vol.19 No.4

Radiotherapy service has seen a spur of interest in the health care system. Many cancer centers aim to develop and enhance radiotherapy service to support the increasing demand. Because Thailand is a developing country, some cancer centers still have limited resources, both staff and machinery, while the number of cancer patients in Thailand has increased every year. To enhance the operational efficiency of radiotherapy service, this research aims to propose an integrated simulation approach and theory of constraints (TOC) approach for increasing radiotherapy service capability in Thailand. As simulation and TOC were applied in the case study, the real bottlenecks were identified in each treatment room. Considering four treatment rooms, only two rooms were selected for improvement (Room 2 and Room 3) after the simulation. The eight proposed solutions concentrated on improving both human- and machine-related bottlenecks. The simulation experiments were conducted to evaluate each solution. The results presented the best solution as adding one technician to Room 3 and replacing the radiation machine in Room 2 with the same machine as in Room 3. With this solution, the number of patients served was increased by 12.32% from the current system. As for the investment needed, the benefit-cost ratio and payback period were calculated as 1.89 and 2.80 years, respectively, for this solution.